Matrix Inversion

2. The apparatus according to claim 1 , wherein the Neumann series expansion for the k terms is mathematically expressed as: A - 1 = ∑ n = 0 k - 1 ⁢ ⁢ ( - D - 1 ⁢ E ) n ⁢ D - 1 + ( - D - 1 ⁢ E ) x ⁢ G - 1 , where A represents the matrix information, D represents the diagonal matrix information, E represents the off diagonal matrix information, and G represents outer Gram matrix information.

5. The apparatus according to claim 1 , wherein the matrix inversion module is for a linear zero-forcing detector.

6. The apparatus according to claim 1 , wherein the matrix inversion module is for a minimum mean-square error detector.

7. The apparatus according to claim 1 , further comprising: a precoding matrix module; wherein the matrix inversion module is coupled to provide the approximation of the inversion of the matrix information to the precoding matrix module.

8. The apparatus according to claim 7 , further comprising a precoder coupled to the precoding matrix module and a plurality of antennas.

9. The apparatus according to claim 8 , wherein the precoder and the plurality of antennas is for large-scale multiple-in, multiple-output (“MIMO”) communication.

11. The method according to claim 10 , wherein the Neumann series expansion for the k terms is mathematically expressed as: A - 1 = ∑ n = 0 k - 1 ⁢ ⁢ ( - D - 1 ⁢ E ) n ⁢ D - 1 + ( - D - 1 ⁢ E ) k ⁢ G - 1 , where A represents the input matrix information, D represents the diagonal matrix information, E represents the off diagonal matrix information, and G represents outer Gram matrix information.

14. The method according to claim 10 , wherein the decomposition block and the expansion block processor are of a matrix inversion module of a linear zero-forcing detector.

15. The method according to claim 10 , wherein the decomposition block and the expansion block processor are of a matrix inversion module of a minimum mean-square error detector.

16. The method according to claim 10 , wherein the decomposition block and the expansion block processor are of a matrix inversion module coupled to a precoding matrix module for large-scale multiple-in, multiple-output (“MIMO”) communication.